Quantifying the effect of geomorphology on aeolian dust emission potential in northern China |
| |
| Authors: | Mengchun Cui Huayu Lu Giles FS Wiggs Vicken Etyemezian Mark R Sweeney Zhiwei Xu |
| |
| Institution: | 1. School of Geography and Ocean Science, Nanjing University, Nanjing, China;2. School of Geography and the Environment, University of Oxford, Oxford, UK;3. Division of Atmospheric Science, Desert Research Institute, Las Vegas, NV, USA;4. Department of Sustainability & Environment, University of South Dakota, Vermillion, SD, USA |
| |
| Abstract: | Representation of dust sources remains a key challenge in quantifying the dust cycle and its environmental and climatic impacts. Direct measurements of dust fluxes from different landform types are useful in understanding the nature of dust emission and characterizing the dynamics of soil erodibility. In this study we used the PI-SWERL® instrument over a seasonal cycle to quantify the potential for PM10 (particles with diameter ≤10 μm) emission from several typical landform types across the Tengger Desert and Mu Us Sandy Land, northern China. Our results indicate that sparse grasslands and coppice dunes showed relatively high emission potentials, with emitted fluxes ranging from 10?1 to 101 mg m?2 s?1. These values were up to five times those emitted from sand dunes, and one to two orders of magnitude greater than the emissions from dry lake beds, stone pavements and dense grasslands. Generally, PM10 emission fluxes were seen to peak in the spring months, with significant reductions in summer and autumn (by up to 95%), and in winter (by up to 98%). Variations in soil moisture were likely a primary controlling factor responsible for this seasonality in PM10 emission. Our data provide a relative quantification of differences in dust emission potential from several key landform types. Such data allow for the evaluation of current dust source schemes proposed by prior researchers. Moreover, our data will allow improvements in properly characterizing the erodibility of dust source regions and hence refine the parameterization of dust emission in climate models. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd. |
| |
| Keywords: | PM10 dust emission northern China seasonality PI-SWERL |
|
|
